Development and Prediction of Flame Retarded Particleboard Fire Behaviour in Real Scale

Authors

  • O.T. Suoware
  • S.I. Umeh Department of Mechanical Engineering, University of Nigeria, Nsukka, NIGERIA
  • S.O. Edelugo African Centre for Excellence, ACE-SPED, University of Nigeria, Nsukka, NIGERIA

Keywords:

Flame retardant, Particleboard, Convolution model, Real scale fire

Abstract

Particleboard composites for building application has become very attractive because of their huge benefits which includes but is not limited to low cost, lightweight, durability and environmental benign. However, the vulnerability of these composite types when exposed to fire restricts their use in areas where stringent fire safety conditions may not apply.  Experimental determination at bench scale of composite particleboard fire behaviour has shown that the addition of flame retardants (FR) can delay the start and spread of fire. Bench scale data obtained in the cone calorimeter (CC) may not represent accurately a real scale fore behaviour during a fire scenario as documented by various researchers. The convolution model is a significant tool for predicting in real scale, fire behaviour of composites which depends on experimental inputs from CC data. In this paper, particleboards made from wood sawdust reinforced polyester composite were processed with FR at 0, 15 and 18% loading ratio using compression moulding technique. Test specimens cut from the FR-particleboards was exposed in horizontal orientation in the CC at 50kW/m2 to obtain experimental data and these were used as inputs to the prediction model. The predictive tool was used to predict the heat released rate and smoke production rate for the FR-particleboard. The results obtained shows that the FR-particleboard contributes very limited fire in real scale and compares well based on Euro-classification with particleboards from literature.

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Published

2021-08-29

Issue

Section

Chemical, Industrial, Materials, Mechanical, Metallurgical, Petroleum & Production Engineering